@inproceedings{68e939c63f8646d1adbeb980bbec930f,
title = "RaCon: A gesture recognition approach via Doppler radar for intelligent human-robot interaction",
abstract = "As an important entrance for human-robot interaction, the hand gesture recognition based on wireless sensor has received great attention in recent years. By recognizing fine-grained arm movements, remotely deployed collaborative robot could work more accurately to satisfy human demands. Existing approaches mostly use wearable sensors or wireless devices to recognize human movement, which is with strict position requirements. In this paper, we propose a robust gesture recognition method based on double Doppler radars. Specifically, we use two Doppler radars to collect two sources of doppler signal of a gesture. Then 6 types of gestures with different angles between people and the radar were classified by employing an improved dynamic time warping (DTW) algorithm. Furthermore, we demonstrate the practicability of the proposed method by developing a cooperative robot control system and the average recognition accuracy is 96%.",
keywords = "Doppler radar, Gesture recognition, Human-robot interaction, Signal synthesis analysis, Wireless sensing",
author = "Kaijie Zhang and Zhiwen Yu and Dong Zhang and Zhu Wang and Bin Guo",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020 ; Conference date: 23-03-2020 Through 27-03-2020",
year = "2020",
month = mar,
doi = "10.1109/PerComWorkshops48775.2020.9156109",
language = "英语",
series = "2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020",
}